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Two-Way Analysis of Variance: Statistical Tests and Graphics Using R

In statistics, analysis of variance (ANOVA) is a collection of statistical models used to distinguish between an observed variance in a particular variable and its component parts.  In its simplest form, ANOVA provides a statistical test of whether or not the means of several groups are all equal, a...

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Detalles Bibliográficos
Autor principal: MacFarland, Thomas W
Lenguaje:eng
Publicado: Springer 2012
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-1-4614-2134-4
http://cds.cern.ch/record/1499247
Descripción
Sumario:In statistics, analysis of variance (ANOVA) is a collection of statistical models used to distinguish between an observed variance in a particular variable and its component parts.  In its simplest form, ANOVA provides a statistical test of whether or not the means of several groups are all equal, and therefore generalizes a test between these groups. One test often used by statisticians and researchers in their work is the Two-Way ANOVA, which determines the differences--and possible interactions--when variables are presented from the perspective of two or more categories.  When a Two-Way ANOVA is implemented, it enables one to compare and contrast variables resulting from independent or joint actions. This brief provides guidance on how R can be used to facilitate Two-Way ANOVA for data analysis and graphical presentation.  Along with instruction on the use of R and R syntax associated with Two-Way ANOVA, this brief will also reinforce the use of descriptive statistics and graphical figures to complement outcomes from parametric Two-Way ANOVA.